



'''simple docstring'''

import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_deebert

from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow


logging.basicConfig(level=logging.DEBUG)

SCREAMING_SNAKE_CASE__     :						Any	=  logging.getLogger()






def 				a  (     )       ->	Any:
		snake_case__	     =argparse.ArgumentParser()
		parser.add_argument('-f'			)
		snake_case__	     =parser.parse_args()
		return args.f


class 							a__( snake_case__     ):






			def 						_lowercase  (     self						)							->							None:
					snake_case__	     =logging.StreamHandler(sys.stdout						)
					logger.addHandler(_UpperCAmelCase						)






			def 						_lowercase  (     self					,   _UpperCAmelCase						)							->							List[str]:
					snake_case__	     =get_gpu_count()

					if n_gpu > 1:
							pass
							# XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560
							# script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py"
							# distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split()
							# cmd = [sys.executable] + distributed_args + args
							# execute_subprocess_async(cmd, env=self.get_env())
							# XXX: test the results - need to save them first into .json file
					else:
							args.insert(0					,   'run_glue_deebert.py'						)
							with patch.object(_UpperCAmelCase					,   'argv'					,   _UpperCAmelCase						):
									snake_case__	     =run_glue_deebert.main()
									for value in result.values():
											self.assertGreaterEqual(_UpperCAmelCase					,   0.666						)






			@slow
			@require_torch_non_multi_gpu
			def 						_lowercase  (     self						)							->							Optional[int]:
					snake_case__	     ='\n            --model_type roberta\n            --model_name_or_path roberta-base\n            --task_name MRPC\n            --do_train\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --max_seq_length 128\n            --per_gpu_eval_batch_size=1\n            --per_gpu_train_batch_size=8\n            --learning_rate 2e-4\n            --num_train_epochs 3\n            --overwrite_output_dir\n            --seed 42\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --save_steps 0\n            --overwrite_cache\n            --eval_after_first_stage\n            '.split()
					self.run_and_check(_UpperCAmelCase						)

					snake_case__	     ='\n            --model_type roberta\n            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --task_name MRPC\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --max_seq_length 128\n            --eval_each_highway\n            --eval_highway\n            --overwrite_cache\n            --per_gpu_eval_batch_size=1\n            '.split()
					self.run_and_check(_UpperCAmelCase						)

					snake_case__	     ='\n            --model_type roberta\n            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --task_name MRPC\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --max_seq_length 128\n            --early_exit_entropy 0.1\n            --eval_highway\n            --overwrite_cache\n            --per_gpu_eval_batch_size=1\n            '.split()
					self.run_and_check(_UpperCAmelCase						)









'''simple docstring'''

from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
			if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			from ...utils.dummy_torch_and_transformers_objects import UnCLIPImageVariationPipeline, UnCLIPPipeline
else:
			from .pipeline_unclip import UnCLIPPipeline
			from .pipeline_unclip_image_variation import UnCLIPImageVariationPipeline
			from .text_proj import UnCLIPTextProjModel




